MLOps Engineer

Key Responsibilities :

- Design and implement robust and scalable ML pipelines on Azure (using Azure ML, Azure Data Factory, Azure DevOps, etc.)

- Automate model training, validation, deployment and retraining workflows.

- Manage and monitor models in production (versioning, drift detection, retraining triggers).

- Implement CI/CD pipelines tailored for ML workloads.

- Exposure on Integrating LLMs into applications with frameworks like LangChain.

- Implementation of Orchestration framework for building and managing agentic System.

- Collaborate with Data Science and Engineering teams to ensure smooth integration of models with applications and APIs.

- Handle data ingestion and transformation pipelines using Azure Data Lake, Databricks, or Synapse.

- Apply best practices in security, performance, and cost optimization in Azure cloud environments.

- Troubleshoot and resolve deployment and model performance issues.